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BMCBI
2008
130views more  BMCBI 2008»
13 years 5 months ago
Function approximation approach to the inference of reduced NGnet models of genetic networks
Background: The inference of a genetic network is a problem in which mutual interactions among genes are deduced using time-series of gene expression patterns. While a number of m...
Shuhei Kimura, Katsuki Sonoda, Soichiro Yamane, Hi...
JCB
2006
185views more  JCB 2006»
13 years 5 months ago
Bayesian Sequential Inference for Stochastic Kinetic Biochemical Network Models
As postgenomic biology becomes more predictive, the ability to infer rate parameters of genetic and biochemical networks will become increasingly important. In this paper, we expl...
Andrew Golightly, Darren J. Wilkinson
CIBCB
2009
IEEE
13 years 6 months ago
Steady-state analysis of genetic regulatory networks modeled by nonlinear ordinary differential equations
Although Ordinary Differential Equations (ODEs) have been used to model Genetic Regulatory Networks (GRNs) in many previous works, their steady-state behaviors are not well studied...
Haixin Wang, Lijun Qian, Edward R. Dougherty
NIPS
2008
13 years 6 months ago
Accelerating Bayesian Inference over Nonlinear Differential Equations with Gaussian Processes
Identification and comparison of nonlinear dynamical system models using noisy and sparse experimental data is a vital task in many fields, however current methods are computation...
Ben Calderhead, Mark Girolami, Neil D. Lawrence